242 | 大卫·克拉考尔谈复杂性、能动性与信息

我想，只要我们掌握的信息不完整，这两种方法对复杂系统都不太适用。

And that, I guess, neither one of these moves really works for a complex system as long as we have incomplete information.

对吧？

Right?

是的。

Yeah.

没错。

That's right.

我是说，目前还没有人真正成功地写出一个作用泛函。

I mean, no one has really succeeded in writing down an action functional.

你可以尝试，而且确实有人在做这方面的努力，比如思考所谓的'行动感知循环'的不同形式化表达，最近流行的版本是自由能原理。

I mean, you can try, and there are efforts if you think about, you know, different formalizations of what's called the action perception loop, the most recent popular version being the free energy principle.

它们确实具有那种变分特性。

They do have that kind of variational character.

实际上，我的一些关于个体性的研究也在最大化某个量，但不确定它是否是某个问题的稳态解。

Even some of my work, actually, on individuality maximizes something, but it's not clear that it's the stationary solution to something.

所以对我来说，它们从根本上不应被视为等同的原因在于，其中一方本质上是在运用守恒与对称性的理念。

And and I So in a way, for me, I mean, the reason why they really fundamentally should not be considered equivalent is because one of them is essentially leveraging ideas of conservation and symmetry.

确实。

Exactly.

对。

Right.

没错。

Right.

而我们生活的世界，你知道，这个复杂的现实世界，充满了对称性破缺和冻结的偶然性。

Whereas the world that we live you know, the complex world we live in is all about broken symmetry and frozen accidents.

正因如此，往好了说，这最多只能算是一种薄弱的隐喻。

And because of that, at best, it would be a sort of weak metaphor.

我发现上网查询最大熵和最小熵原理特别令人沮丧，因为存在各种相互矛盾的原则——有时熵要最大化，有时又要最小化。

I found it very frustrating to kind of go to the Internet and look up principles of maximum entropy and minimum entropy, because there's all sorts of principles that say, sometimes entropy is maximized, sometimes it's minimized.

我们并不完全清楚何时该用哪种。

We're not exactly sure when.

我不太确定这些概念的实际用途，但我仍然觉得其中可能有些价值。

I'm not quite sure what the usefulness of these these ideas are, but I still feel there's probably something there.

我只是还没能确切把握到它。

I just haven't put my finger on it yet.

是的。

Yeah.

我完全同意，我认为这就像所有事情一样，你必须将概念操作化。

I completely agree, and I think that it's like everything, right, that you have to operationalize the concept.

一旦你这样做了，就能以某种方式与现实联系起来，使其变得有用。

And once you've done that, you're tethered to reality in a way that it's useful.

我认为如果用这些非常笼统的术语讨论，很多人都会这样，我也不太确定到底在说什么。

I think if you talk in these very generic terms, I think many people do, I'm not exactly sure either what what is being said.

不过，我很高兴你提到麦克斯韦妖，那是我最喜欢的讨论话题之一，我不确定听众是否知道我们花了数十年时间才对其正确解释达成某种共识。

Well, I'm really glad that you mentioned Maxwell's demon though, because that is another one of my favorite talking points, and I'm I'm not sure if if the listeners know how it took many many many decades to come to some viewpoint on what the right explanation for.

我就假设大家都知道麦克斯韦妖是什么了。

I'm gonna assume people know what Maxwell's demon is.

就是那个能通过分离热原子和冷原子，看似违反热力学第二定律的小恶魔。

Is, know, a little demon that can seemingly violate the second law by separating hot atoms and cold atoms.

我们花了很长时间才搞明白它可能并没有真正违反第二定律，但直到现在人们仍有分歧。

It took us a long while to figure out how maybe that's not really violating the second law, and even now, people don't agree.

我不确定我们是否已经完全解决了这个问题。

I'm not quite sure that we're completely done.

但无论如何，我不会说它违反了第二定律，而是将其视为多种复杂系统的范式。

But one way or another, I wouldn't call it violating the second law, but it is a paradigm for many kinds of complex systems.

对吧？

Right?

某种利用自由能使事物保持比自然状态更高组织度的机制。

Something that uses free energy to keep things more organized than they otherwise would.

你觉得这个说法合理吗？

Do you do you think that's fair?

哦，完全同意。

Oh, absolutely.

确实如此。

I do.

而且正如你所知，这正是我深入研究过的领域。

And I and as you know, this is something I've worked on quite a bit.

为了进一步延伸你的解释，很明显的是——如果你将麦克斯韦妖视为一种分类机制，正如你所说在热粒子与冷粒子之间进行筛选，若将这个思想实验反过来思考，你可以把自然选择看作是在环境中筛选不同变体的‘妖’。

And I just to to extend your explanation, what's quite clear is that if you think about Maxwell's edema as as a mechanism of sorting, as you said, between hot and cold particles, if you turn that little thought experiment on its head, you can think about natural selection as edema that sorts between alternative variants in an environment.

而复杂系统给这个故事增加的复杂性在于——我们就是妖本身的起源。

And what is added to the complication of this story in complex systems is we is the origin of the demon itself.

正是如此。

Exactly.

看，对吧？

See, when right?

当麦克斯韦和开尔文勋爵思考这个问题时，它更像是一种思想实验。

When when Maxwell and Lord Kelvin were thinking about it, it was a sort of a Gedanken.

就像是，好吧。

It was like, okay.

这就是你如何可以违反这条统计定律。

Here's how you can violate this statistical law.

然后事实证明，好吧，齐拉尔，我当时就觉得不是这样的。

And then it turns out, well, Zilar, I was like, no.

实际上，这个恶魔也在散发热量，诸如此类。

The demon is actually, you know, dissipating heat too and so on and so forth.

但在生物学领域，如果你要玩弄恶魔——就像我和许多人做的那样，它们被称作不同的名字——那么你必须解释它们的起源。

But in the biological domain, if you're gonna play with demons, which I do and as many people do, and they get called different things, then you have to account for their origin.

而自然选择是一个非常有趣的集体恶魔。

And natural selection is a very interesting collective demon.

我的意思是，自然选择确实有物理层面的影响。

I mean, certainly, there's a physical dimension to natural selection.

如果你是一只鸟在飞翔，让你停留在空中的并不是另一只鸟。

If you're a bird and you're flying, it's not another bird that's keeping you in the air.

但对我们大多数人以及我们关心的结构来说，它们是通过与其他生物的竞争形成的。

But for most of us and for most of the structure that we care about, it came about through competition with other living things.

嗯

Mhmm.

恶魔

Demons.

所以我们彼此都是相互的恶魔，而发展这套关于嵌套层级恶魔的理论一直是我感兴趣的课题。

So we're all mutual demons to each other, and developing that theory of nested hierarchical demons has been of an interest of mine.

结果发现这很困难，顺便说一句，这种困难不亚于你那个咖啡隐喻的难度，因为现在让我想想。

And it turns out to be difficult, not unlike the difficulty incidentally of your coffee metaphor because now let me see.

我接下来可能要讲得稍微专业一点，肖恩，你告诉我这是否——

I'm gonna maybe a little bit more technical now, you tell me, Sean, whether this

我会告诉你的。

I will tell you.

请先讲专业内容，我们稍后再调整。

Please be technical first, and we'll fix it later.

好的

Yeah.

即以下内容。

Which is the following.

对吧？

Right?

如果你想象一根二进制字符串，我们把每个比特称为一个承载信息的自由度。

Which if you imagine a string, a binary string, let's call each of those bits an information bearing degree of freedom.

它确实有作用。

It it does something.

第一个比特告诉你向左转。

The first bit tells you to go left.

第二个比特告诉你该开哪扇门，诸如此类。

The second bit tells you which door to open, you know, that kind of thing.

而根据第二定律我们知道，如果长时间不干预这个字符串，它就会完全被打乱。

And we know, because of the second law, that if you leave that string alone for long enough, it'll just be all shuffled.

它会被随机化、热化。

It's randomized, thermalized.

那么想象一下基因组。

So think about a genome.

它就像一串信息，每个比特都是承载信息的自由度。

It's like a string, and each of the bits is an information bearing degree of freedom.

它编码了蛋白质的氨基酸或结合位点等等。

It encodes an amino acid of a protein or binding site or okay.

因此，每一个在多个世代中可靠传递的比特，都必须有某种机制检查并说：保持原样。

So for every bit that is transmitted over many generations reliably, something has to inspect it and say, stay that way.

嗯。

Mhmm.

这就是自然选择。

That's natural selection.

对吧？

Right?

但这不是一个单一的‘恶魔’在操作。

But it's not one demon.

要知道，它是一棵树。

You know, it's a tree.

它是一只蚂蚁。

It's an ant.

它是你周围环境中的水量。

It's it's the amount of water in your environment.

这是一个极其复杂的复合力量体系，在检验每一个比特。

It's an incredibly complicated composite of forces inspecting each bit.

事实证明，你可以证明这一点，目标序列的复杂性或描述长度，不能超过自然选择本身的描述长度。

And turns out, you can prove this, that the complication or the description length of the target sequence, right, cannot be greater than the description length of natural selection itself.

因为自然选择必须检查每一个位。

Because natural selection has to inspect each bit.

对吧？

Right?

除非你能压缩它。

Unless you can compress it.

如果存在冗余，你就能做到。

If there's redundancies, you can.

因此你得到了这个非常奇怪的结果：生物体的复杂性、智能体的复杂性，其上限受限于自然选择本身的复杂性。

And so you get this really weird result, which is that organismal complexity, agent complexity is upper bounded by the complexity of natural selection itself.

这就是关于‘恶魔起源’的问题。

And that's this problem of the origin of the demon.

因为你必须构建这个该死的东西。

Well Because you have to build this damn thing.

对。

Right.

但你需要向我解释一下，我们所说的‘自然选择本身的复杂性’是什么意思。

But you're gonna need to explain to me what we mean by the complexity of natural selection itself.

我是说，自然选择的概念可以用俳句的形式来表达。

I mean, the the idea of natural selection can be written in haiku form.

对吧？

Right?

你是说，你必须指的是否将选择发生的整个环境都包括在内？

I mean, you must mean the are you including the whole environment in which the selection is happening?

是的。

Yes.

嗯，那就是自然选择。

Well, that is natural selection.

对吧，肖恩？

Right, Sean?

这就是使用‘自然选择’这个词稍微有些误导性的地方之一，因为它基本上涵盖了宇宙中的每一种力量

That's one of the slightly misleading things about using the word natural selection because it's basically every force in the universe

没错。

Right.

那些干扰每个信息承载片段的力量。

That intrudes upon each bit that's information bearing.

所以这是个非常容易让人误解的概念。

So it's a very misleading idea.

事实上，这正是数学的局限性之一，某种程度上类似于适应度景观的局限，因为你只需写下这个东西并称之为f下标i。

And in fact, that's partly one of the limitations of the mathematics, a little bit like the limitation of the fitness landscape, because you can just write down this thing and call it f sub I.

不。

No.

没问题。

The no problem.

如此简单。

So simple.

但那是什么东西呢？

But what is that thing?

那个东西就是一切。

And that thing is everything.

对。

Right.

换种更清晰的说法，如果我给你一个随机字符串，然后对你说，肖恩，我希望你通过翻转比特来达成这个目标字符串。

So another way to make this clearer is if I gave you a random string and I said to you, Sean, I would like you to flip the bits to achieve this target string.

而且每次也都是随机的，你得逐位遍历那个序列，相应地翻转。

And each time that was also random, you'd have to go through that sequence bit by bit, flipping accordingly.

嗯。

Mhmm.

你就是自然选择。

You're natural selection.

我是那个生物体。

I'm the organism.

所以你能看出这里有个挺有趣的问题。

So you can see there's this kind of interesting problem.

因此，才发展出生态系统工程和生态位构建这类概念——这些努力部分地试图超越认知去构建自然选择本身。

Hence, the development of ideas like ecosystem engineering and niche construction, which are efforts partial beyond belief to build natural selection itself.

选择的起源，而非物种的起源。

The origin of selection, not the origin of species.

在我电脑的某个地方，存着我未来研究项目的清单。

So somewhere on my computer, I have a list of my future research projects.

我不知道你怎么想，但我总是以未来可能撰写的论文标题来构想我的研究目标。

I don't know about you, but I always I conceptualize my future research goals in terms of the titles of papers that I will someday try to write.

嗯，是的。

And Yeah.

其中一些目标已经规划得非常详尽，而另一些则完全是推测性的。

And one of them is some of them are very well fleshed out and some of them are completely speculative.

在后一类中，有一个课题是‘信息如何获得生命’。

In the latter category, we have how information comes to life.

我想知道——我觉得这正是你在探讨的问题。

I I want to know I I think this is exactly the question you're asking.

在宇宙及其内部生命的演化过程中，第一个瞬间是什么时候，宇宙的某一部分开始为了某种目的而利用另一部分的信息？

What is the first moment in the evolution of the universe and the life within it where one part of the universe was using information about another part for some purpose?

这个问题——我们已经有答案了吗？

Is that something do we know the answer to that one already?

没有。

No.

好的。

Okay.

不知道。

No.

这真的很有趣。

That's really interesting.

这确实很奇怪。

It's it's odd.

你知道吗？

You know?

克里斯·肯普西斯和我刚写了一篇论文，题为《生命是解决问题的物质》。

Chris Kempis and I just wrote a paper called Life is Problem Solving Matter.

而且，你知道，我们可以深入探讨这个话题，但我认为你的思考方向是正确的，因为我们通常思考生命起源的方式——也就是你提到的嗯哼。

And, you know, this is a whole we can go down this path, but I think the way that you're thinking about it is correct because the way we typically think about origin of life, which is what you're talking about Mhmm.

是指某些与生命相关的特定化学过程的起源。

Is the origin of certain kinds of chemistry which are correlated with life.

对吧？

Right?

因此我们常常将生命本身的化学过程混淆，但生命确实在做你所描述的那种事，即某种奇特的推理表征行为。

And so we often confound the chemistry of life itself, but life is doing the thing you're describing, which is some weird inferential representational thing.

当那首次发生时，我认为这确实是个谜。

And when that first happened, I think it's genuinely mysterious.

我确实认为我们被对有机化学的痴迷稍微误导了。

I do think we've been a little bit misled by an obsession with organic chemistry.

需要指出的一点是，我认为我们已经多次构建了非化学的、数字形式的生命，这对我们很有帮助。

And one thing to point out that helps us is I think we've built life so many times as nonchemical, digital life.

肖恩，如果你在电脑上写一小段代码，我认为那可以是一种非常简单的生命形式，但我觉得它符合生命的定义。

I think that if you write a little code in your computer, Sean, it it could be very simple form of life, but I think it qualifies.

生命是种奇特的东西——借用物理概念来说，我主要研究两个领域：生命与智能。

And the life is this weird thing just to use a physics concept, which things I two things I kind of work on, life and intelligence.

我认为生命是内聚性的，而智能则是外延性的。

Life, I consider intensive, whereas intelligence, I consider extensive.

拥有100个细胞并不比拥有1个细胞更富有生命力。

You're not more alive if you have a 100 cells than one.

对。

Right.

对吧？

Right?

是的。

Yeah.

大象并不比跳蚤更有生命力。

An elephant is not more alive than a flea.

那样想就有点荒谬了。

That that would be kind of silly.

但大象可能比跳蚤更聪明。

But but you but an elephant might be more intelligent than a flea.

这两个概念之间存在着非常有趣的联系。

And there's this very interesting connection between those two concepts.

我认为你不能将它们独立对待。

I don't think that you can treat them independently.

我认为一旦生命发展出智能，反之亦然，而要区分这两者是非常复杂的。

I think once you develop life, develop intelligence and vice versa, and working out that difference is is is complicated.

所以我总是从熵、第二定律、核心筛选等角度来思考这些问题。

So I always just think about these things in terms of entropy and the second law and core screening and things like that.

信息在你所谈论的一切中的核心地位非常明显。

The centrality of information to everything that you've talked about is is very clear.

对我而言，从某种意义上说，大爆炸是终极的信息资源。

And to me, the big bang is the ultimate information resource in some sense.

它的熵非常非常低，换句话说，我们对当时的状态掌握着大量信息。

It was very, very low entropy, which is another way of saying that we have a lot of information about exactly what the state was.

而自那以后的一切，都只是在探索可能性空间。

And ever everything ever since then is just exploring the space of of possibilities.

你知道，当我思考复杂系统的演化时，我会想到这些简单的无机系统。

And is it you know, I I the the evolution of complex systems, you know, I I think about these simple inorganic ones.

你需要思考目的性智能体的演化过程。

You want to think about the evolution of telenomic agents.

是否存在一种普遍理解，解释它们为何会在第二定律的总体运作中出现？

Is there a general understanding of why they come to be at all in that general working out of the second law?

没有。

No.

现有的理解更像是一种同义反复：一旦一个能够纠错的复制者出现，它就会持续存在。

What there is is a sort of tautological understanding that once a replicator comes into existence that can error correct, it will stay in existence.

你明白我的意思吗？

You know what I mean?

是的。

Yeah.

但这并不一定代表它对所处世界有复杂的编码认知。

So but that's not necessarily a sophisticated encoding of of the world in which it lives.

而我们面对的这种状况，某种程度上就像大型语言模型回形针噩梦那样。

And you we can it's the sort of large language model paperclip nightmare.

对吧？

Right?

就是这类情况。

It's that sort of thing.

你可以构建大量简单的东西，这相当直接明了。

You can build lots and lots of simple things, and it's quite straightforward.

但这种转向编码其他事物的趋势，其中存在各种说法。

But this move towards encoding something else that's encoding, there are stories.

对吗？

Right?

你看，这是竞争性的，如果我能比你更擅长编码，你懂吧？

You know, well, look, it's competitive and if I can out encode you, then you know?

但这些都只是说法，我真的不知道有什么理论依据。

But they're stories, and I don't I genuinely don't know of any theory.

我知道有些模型，但它们对我来说有点过于精细调校了。

I know of models, but they're a little bit too fine tuned to my you know, for my tastes.

但我认为并不存在一种理论声称越来越复杂的目的性主体应当出现。

But I don't think there is a theory that says that more and more sophisticated telenomic agents should come into existence.

我不认为存在这样的理论。

I don't think there is such a theory.

部分

Part of

部分原因在于，我与SFI的迈克尔·拉赫曼就这个问题进行过一些讨论。

it part of it is and I talked a little bit with Michael Lachman at SFI about this question.

在我看来，这个谜题的一种表述方式是：在统计力学、热力学和熵的层面上，宇宙中并不存在未来的边界条件。

Yet to me, one way of stating the puzzle is at the level of just statistical mechanics and thermo and entropy, there is no future boundary condition in the universe.

宇宙只是随心所欲地做它想做的事。

It's just that the universe does whatever it was it wants to do.

存在一个过去的边界条件，即低熵的过去假说、大爆炸等等。

There's a past boundary condition, the low entropy, past hypothesis, big bang, etcetera.

但或许可以将有目的的主体视为——我不确定，如果我错了请纠正——携带着一个小小的未来边界条件。

But purposeful agents can be thought of maybe, I don't know, tell me if I'm wrong, as carrying a little mini future boundary condition with them.

他们想要在未来达到某种状态，几乎不在乎如何到达那里。

There is a a state they want to be at in the future, and it almost doesn't matter how they get there.

对吧？

Right?

比如，如果我想去商店，可能开车、步行或选择某条路线等等。

Like, if I want to go to the store, maybe I, you know, take the car or I walk or I take this path or whatever.

关键在于我想要达到的那个未来状态。

The point is that future state I want to be in.

那么，宇宙中那个庞大的低熵过去边界条件，是如何转变为具有目的性的主体所携带的微型边界条件的呢？

So how in the world does the, big looming past boundary condition of low entropy get flipped around to little mini boundary conditions in agents that have purposes?

是啊。

Yeah.

不。

No.

我认为这是个深刻的问题。

I I think it's a deep question.

我真的不认为我有好的答案。

I don't I genuinely don't think I have good answers to it.

我认为，对我来说，这回到了我们之前关于行动和智能体适应的观点，我认为智能体引入了策略的概念，比如马尔可夫策略，即一种程序或路径，这正是你所谈论的。

I think that the I mean, that to me is, you know, going back to our earlier point about action and adaptation to agents, I think agents introduced the concept of the policy, like a Markov policy, meaning a procedure or a route, which is what you're talking about.

如果你考虑趋化性，一个细菌沿着营养梯度游向目标，这是一个微分控制器，即时判断标量场告诉你处于正确位置，你会稍微摆动，一旦到达更高浓度区域就会停止等等。

And I think that if you think about chemotaxis, a bacterium that navigates up some nutrient gradient to a target, It's this differential controller where you think instantaneously, the scalar field tells me that I'm in the right place, and I'm gonna wiggle about a bit and stop once I get to a higher concentration and so forth.

但那不是我们的行为方式。

But that's not what we do.

对吧？

Right?

我们会说，我想去商店买些橙汁。

We say, you know, I I wanna go to the shop and buy some orange juice.

对吧？

Right?

而且并不存在什么梯度。

And there is no gradient.

对吧？

Right?

并没有某种诡异的橙汁标量场信息告诉我离Whole Foods超市更近了。

There is no information in some weird orange juice scalar field telling me I've got closer to Whole Foods.

没有。

No.

可惜啊。

Sadly.

所以我有一张地图。

So I have a map.

而这种从简单适应到遵循策略的能动性转变非常引人入胜。

And and that transition from adaptation, simple adaptation to agency following a policy is very intriguing.

毫无疑问，我们可以建立模型，在某种意义上积累能让你编码路径的信息片段。

No doubt we could build models where you, in some sense, accumulate bits of information that allow you to encode a path.

但你知道，是否存在关于这种转变的理论呢？

But, you know, is there a theory for that transition?

不。

No.

好的。

Okay.

我认为要提出更聪明的问题，我们应该先讨论一下涌现现象，因为...

I think to ask more intelligent questions, we we should get some stuff on the table about emergence because Yeah.

你知道，你经常谈论这个话题。

You know, you've talked about it a lot.

我也经常谈论它。

I've talked it about a lot.

这个词充满争议。

The word is fraught.

与其试图定义它，不如让我问问你是如何看待涌现这个概念的。

So rather than trying to define it, let me ask how you think about the idea of emergence.

是的。

Yeah.

在此我要特别感谢菲尔·安德森和鲍勃·劳克林。

And I and I'm very indebted to Phil Anderson here and and and Bob Laughlin.

是的。

The yeah.

这个词不知为何总是招来许多胡说八道的评论。

It's one of those terms that, for some reason, attracts a lot of bullshitty commentary.

让我从简单的开始，再逐步深入。

And let me make start simple and get more complicated.

很好。

Perfect.

我认为最简单的切入点就是菲尔提出的对称性破缺。

I think the simplest place to start is where Phil begins with symmetry breaking.

即物理学的基本定律本质上是具有对称性的。

And that is the underlying fundamental laws of physics are symmetric.

因此，当你试图解释为何选择某个特定状态而非另一个（根据定律两者概率相等时），就必须引入对称性破缺的概念——无论是外力驱动还是通过热力学随机涨落内生形成，最终由某种能垒将系统维持在该状态。

And so if you're trying to explain why one particular stage is picked rather than another, where both would be equally probable under the laws, you have to invoke this idea that asymmetry is broken, either it's driven or it's endogenously found by thermistochastic fluctuation, and then there is some energy barrier that keeps you in that state.

而通常给出的经典例子总是分子的手性，无论它们是左旋还是右旋。

And and the canonical examples always given are the chirality of molecules, whether they're left handed or right handed.

氨基酸是L型手性的，它们是左旋的，而糖类是D型手性的，它们是右旋的。

And amino acids are L chiral, they're left handed, and sugars are de chiral, they're right handed.

而且它们总是如此。

And they always are.

因此，物理学中没有任何定律表明这应该是正确的，因为它们有对映体，所以你应该会发现同样多的LSD。

And so and there's no law of physics that tells you that that should be true because they're they have enantiomers, and so you should find as many LSD.

你不会。

You don't.

现在，这是第一点。

Now so that's the first point.

当然，随着分子变大，隧穿势垒会变得更深，因此这些破缺的对称性会不断累积。

And, course, as molecules get bigger, the tunneling barriers get deeper, and so these broken symmetries accumulate.

这就是默里喜欢称之为'冻结的偶然'的现象。

And that's what Murray liked to call frozen accidents.

复杂的世界充满了这些‘冻结的意外’，并且正是由它们构建而成。

And the complex world is full of them, and it's built up from them.

因此，我认为涌现的第一个条件就是对称性破缺，因为它已经表明，如果你想理解可观测现象，无法直接套用物理定律。

So the first, I think, condition for emergence is broken symmetry, because it already tells you that if you want to understand the the observable, you can't use the physics.

物理定律不会告诉你这些。

Doesn't tell you.

但它与物理定律是一致的。

And it's consistent with it.

用他的话说——我认为这是个极其重要的区分——它遵循物理定律，但不受物理定律支配。

It obeys the physics, but it's not dictated by the physics, to use his language, which I think is a very, very important distinction.

遵循与支配的区别。

Obey versus dictate.

当然，随着层级上升，打破所有对称性的正是自然选择。

And and then, of course, as you move up, it's natural selection that's breaking all the symmetries.

所以它遵循物理定律，却由这些奇特的‘恶魔’通过选择来支配。

And and so it's obeying physics, but dictated by selection by these weird demons.

好的。

So okay.

第一点。

Point one.

第二点。

Point two.

事实证明，在这一系列冻结的偶然性层级中，你可以为感兴趣的可观测现象、为有效变量写下有效的理论——不是基础理论，而是有效理论——这些理论在理解所有微观组成部分方面表现得同样出色。

It turns out that in this hierarchy of frozen accidents, turns out that you can write down effective theories, not fundamental theories, effective theories, for the observables of interest, for the effective variables, that do as well as understanding all the microscopic constituents.

例如，你可以写下流体动力学方程，而不是对所有粒子运动进行非常高维度的描述。

And for example, you can write down a fluid dynamical equation as opposed to a very high dimensional description of all the particles' motions.

对吧。

Right.

对我来说，对称性破缺是写下有效理论的物理前提条件。

And for me, broken symmetry is the physical precondition for the possibility of writing down effective theories.

如果这个有效理论在动力学上是充分的——即即使它明显遵循那些定律，你也不会通过向下探究获得更多信息——这就是我们所说的涌现现象。

And if that effective theory is dynamically sufficient, that is you don't gain information by going down, even though it's clearly obeying those laws, that is what we mean by emergence.

这并不复杂。

And it's not very complicated.

它存在于物理世界，也存在于Gumblitz世界。

It's it's in the physical world and it's in the Gumblitz world.

令人着迷的是，目的论物质利用涌现层级来理解自身。

And what's fascinating is that telenomic matter mobilizes emergent levels to understand itself.

所以我们有自我认知的概念，并运用心智去理解它。

So we have a concept of ourselves that we and we mobilize our minds to understand it.

它遵循大脑动力学，但我完全不知道我的神经元在做什么，也不关心。

It obeys brain dynamics, but I have no idea what my neurons are doing and neither do I care.

这种认知方式贯穿了各个学科领域。

And and that extends up through the disciplines.

我喜欢举数学的例子：定理正确性的证明，比如安德鲁·怀尔斯对费马猜想的证明，并不取决于他产生了多少内啡肽。

And I like to give the example, of course, of mathematics that the proof of the correctness of a theorem, like Andrew Wiles' proof of the Fermat conjecture, does not depend on how much endorphin he's generating.

它完全通过数学语言本身来表达。

It's expressed entirely in terms of mathematics itself.

当你能够做到这一点时，为什么允许你写下一种有效理论就是涌现现象有趣的原因，因为你并非总能做到。

And when you can do that, why you're allowed to write down an effective theory is why emergence is interesting because you can't always do it.

当然。

Sure.

对吧？

Right?

因为对吧？

Because right?

因为该理论适用的参数变化范围可能非常有限，这就是为什么我认为这是一个有趣的科学问题，而非必然现象。

Because the range of parametric variation under which that theory applies can be very limiting, and that's why I think it's an interesting scientific problem as opposed to just an inevitable one.

所以我认为这种涌现版本对应了经典强弱涌现的区分，即弱涌现。

So that version of emergence, I think, maps on to the classic distinction of weak versus strong emergence as weak emergence.

你是在谈论对一个本可以在微观层面描述的系统进行粗粒化处理，但你不需要也不值得这么做。

You're you're talking about coarse graining a system that could very well be described at a microscopic level, but you don't need to, and there's no point in doing it.

对吧？

Right?

是的。

Yes.

有些人，也许你认识其中一些，他们认为这还不够，他们真心相信我们需要全新的宏观物理定律，然后通过向下因果关系影响微观层面发生的事情。

There are people out there, maybe you know some of them, who think that's that's not enough, who really think that we're gonna need new laws of physics purely at the macro levels that then influence via downward causation what's happening at the micro level.

你反对这种观点，还是单纯觉得不需要？

Are you against that, or do you just not need it?

我反对，我会解释为什么我反对，理由和菲尔一样，因为这太贪婪了。

I'm against it, and I I'll explain why I'm against it for the reasons that Phil was, which is it's greedy.

那些所谓的物理新定律，其实应该叫英国文学、音乐创作或形而上学，对吧？

Those new laws of physics are called English literature or musical composition or metaphysics, Right?

或者木工活。

Or carpentry.

这算不上物理新定律。

And it's not a new law of physics.

这只是个新理论。

It's a new theory.

而且它可能包含定律。

And it may have laws in it.

我不确定。

I'm not sure.

它可能包含规则。

It may have rules in it.

它或许会稍微谦逊一些。

It might be a little bit more modest.

但它们已不再是物理学了。

But they're not physics anymore.

我认为一旦进入过度复杂的领域，物理学就终结了。

I think physics ended once we moved into the domain of excessive complication.

依然存在。

Still there.

它永远不会消失。

It's never going away.

感谢上帝。

Thank God.

你知道吗？

You know?

谢谢你，简，不管怎样。

Thank you, Jean, whatever.

但这并不太实用。

But it's not very useful.

所以这就是我所说的困惑。

And so this is what I mean by confusion.

其实这不是什么复杂的事情，肖恩。

It's actually not a complicated thing, Sean.

对吧？

Right?

我的意思是，我们可以写下这些有效理论。

I mean, we can write down these effective theories.

我们想知道什么时候可以。

We would like to know when we can.

大概在某个温度范围内它们是适用的。

Presumably, there's some temperature range where they apply.

对吧？

Right?

嗯。

Mhmm.

到某个程度，我的大脑就无法工作了，因为蛋白质会变性。

At a certain point, my mind isn't gonna work because the proteins are gonna denature.

当然。

Of course.

是的。

Yeah.

那我就需要了解蛋白质了。

And then I need to know about proteins.

因此从这个意义上说，我必须成为一个还原主义者。

So I have to be a reductionist in in that sense.

不过这样也好。

But so fine.

这是一门关于多元主义的科学。

It's it's it's it's a science of pluralism.

它解释了为什么我们既需要勋伯格和吉米·亨德里克斯，也不能只有牛顿和莱布尼茨。

It tells you why we need to have Schoenberg and Jimi Hendrix and not just Newton and Leibniz.

所以我觉得这在各方面都令人安心。

So I I find that reassuring in all sorts of ways.

关于下向因果关系，杰西卡对此有过精彩论述——我很欣赏杰西卡·弗拉克的观点，她提到局部通过读取整体状态来运作。

Now in terms of downward causation, you know, and I think Jessica's written about this quite well and which I quite like, Jessica Flack, when she talks about the parts reading off the states of the whole.

我认为这解决了一些悖论元素——比如我可以通过阅读你的著作而受其影响。

And and that, I think, resolves elements of the paradox, right, which is I can read one of your books and be influenced by it.

而我的思维——或者说我的神经元——正在解读这些内容。

And all my my mind is reading it as are my neurons.

这其中已不再有任何机械性的谜团了。

And there's no mechanical mystery in that anymore.

这就是没有神秘色彩的下向因果关系。

And that's downward causation without mystery.

所以我思考这个问题的一个原因是，我们生活在一个事物可能排列组合方式极其多样的世界里。

So what I'm thinking about one of the reasons why I brought up this question is we live in a world where the space of possible arrangements of things is very, very large.

对吧？

Right?

组合可能性的集合超出了我们的理解范围，而我们生活在其中非常特定的位置。

The combinatorial set of possibilities is beyond our our comprehension, and we live in a very specific place in it.

这里有特定的动物、特定的器官环境等等。

There's specific animals, specific organ environments, so forth.

有些人会说，要解释为何我们此刻所处的正是这个特定位置，仅靠微观物理学加上一些随机数字是不够的。

There are those who would say that in order to account for why this particular place we live in right now is where we are, we can't just rely on microscopic physics plus some random numbers.

我们需要一些原则或类似的东西来覆盖它。

We need some principles or something to stretch out over it.

我并没有公正地阐述这个立场，因为我对此毫无信念，但我也没有凭空捏造。

I'm not I'm not doing this position justice because I don't have the slightest belief in it, but there I'm not making it up either.

确实存在持这种观点的人。

There are people like this.

不。

No.

我知道。

I know.

而且我认为，他们这种蒙昧主义中合理的部分是——正如我们之前指出的——我们甚至对生命起源都还不甚了解。

And I and I and I think that the legitimate part of their obscurantism is that we don't really understand as we've already we don't even understand about the origin of life, as we pointed out earlier.

所以确实存在需要解决的真实问题，我们不该假装已经解决了。

So there are genuine problems out there that need to be resolved, and we shouldn't pretend we have.

但我们也不想用...用那些虚无缥缈的东西来填补空白。

And but we don't wanna fill it with fill it with, you know, moonshine.

不过我的确认为，我们可能需要一套更精密的记忆理论和历史理论。

The I do think, though, that we may need a much more sophisticated theory of memory and of history.

所以当你谈到波动等等时，这正是进化的关键所在。

And so when you talk about fluctuations and so forth, that's the whole point about evolution.

对吧？

Right?

它逐步构建出对现实越来越精细的编码。

That it it incrementally builds up a more and more refined encoding of reality.

它构建了记忆。

It builds up a memory.

顺便说，这就是与退相干历史理论等等的联系。

And that's, by the way, the connection to the and decoherent histories and all that.

我的意思是，我们本质上编码了进化史中特定轨迹的粗粒度表征。

I mean, there's this we essentially encode coarse grained representations of particular trajectories in evolutionary history.

你应该解释什么是。

You should explain what an is.

哦，这是对我们刚去世的同事兼朋友吉姆·哈特尔的一点致敬。

Oh, well, this is a little bit of a tribute to our colleague and friend, Jim Hartle, who just passed away.

在《夸克与美洲虎》一书中，默里·盖尔曼用我认同的图式理论描述了复杂系统，这些小实体通过编码历史来指导行为和预测。

In the quark and the jaguar, Murray Gell Mann presents a complex system in lines that I share in terms of schema, these little entities that have that encode histories that they use to behave and to predict.

实际上，他在那本书里并没有深入探讨这个问题。

He doesn't go much beyond that, actually, in that in that book.

我是说，我们可以讨论这个——约翰·霍伦登也谈到过这一点。

We can talk I mean and John Hollenden talked about this.

事实上，第一个图式定理是由伊曼努尔·康德在《纯粹理性批判》中提出的。

And in fact, the first schema theorem was presented by Immanuel Kant in the critique of pure reason.

其中有一整章专门论述图式，康德试图解释如何将连续的感觉转化为命题。

It's a whole chapter called the schema, where Kant was trying to understand how you turned continuous sensation into propositions.

这其实非常引人入胜。

Such fascinating, actually.

这是对复杂性理论的又一史前贡献。

Another prehistoric contribution to complexity.

后来默里提议，我们把这种图式称为IGUS。

And Murray then said, let's call the scheme an IGUS.

这是一个缩写，全称为信息收集利用系统。

And this is an abbreviation, an information gathering utilizing system.

我想默里和我都会非常好奇想听听你对这个的看法，肖恩，因为我觉得这部分是源于他对哥本哈根解释、观察者角色以及所有那些关于意识与单纯探测器之间的怪异现象感到非常不满。

And I think Murray and I would be very here curious to hear what you think about Sean this, Sean, because I think part of this was motivated by his feeling very disgruntled with Copenhagen and the role of the observer and all that weirdness around the consciousness versus just, you know Yeah.

一个探测器。

A detector.

然后吉姆·哈特尔以我认为非常精彩的方式，在两篇我特别喜欢的论文中扩展了这一概念。

And then Jim Hartle, in in really delightful ways, I think, extended the idea in two papers which I really enjoyed.

其中一篇是《为何宇宙是可理解的？》

One of them was why is the universe comprehensible?

触及了爱因斯坦提出的问题。

Getting at Einstein's question.

而第二篇是他称之为《当下的物理学》，探讨为何存在现在、过去与未来。

And and the second one was what he called the physics of now, which was why is there a present, a past, and a future?

这些实际上都是进化过程中的衍生现象。

These are actually evolutionary sequelae.

它们不属于物理学范畴。

They are not part of physics.

它们是复杂系统的一部分。

They're a part of complex systems.

他使用了IGUS，将其置于闵可夫斯基空间中，并说明它将如何运作，并从中推导出这三个概念。

And he used the IGUS he put an IGUS in the Minkowski space and said, this is how it would operate and derive these three concepts from that.

总之，这就是关于吉姆和IGUS的内容。

And anyway, that's just on Jim and the IGUS.

嗯，在播客中即兴发言总是有些冒险，但或许我能看出我所关心的关于熵增的问题——从低熵到平衡态的旅程如何显得复杂——与你提出的关于能动性、信息和目的论的观点之间存在联系，因为这很可能只是从低熵到高熵过程中相互作用的子系统的一个普遍特征，它们会彼此留下印记。

Well, this is always dangerous to sort of speak extemporaneously in the middle of a podcast, but maybe I can see that there is a link between the questions that I care about about increasing entropy and how the journey from low entropy to equilibrium can look complex to the points you raise about agency and information and telenomics because it it it is probably just a generic feature of interacting subsystems along the journey from low entropy to high entropy that they make an impression on each other.

如果我走过沙滩，就会在上面留下脚印。

If I walk down the beach, I leave footprints on it.

虽然沙滩不会利用这些脚印做任何事情，但或许不难想象，如果两个相互作用的系统都具有足够的复杂性，它们若能利用这些信息，就更有可能持续存在。

Now the beach doesn't use those footprints to to do anything, but I it might not be that much of a leap to see how if both of the interacting systems, have enough complexity, they could they're more likely to persist if they can put that information to use.

是的。

Yeah.

我是说，你可以...我是说，我研究过这些模型？

I mean, you can I mean, I've worked on these models?

我是说，这并不难做到。

Mean, it's not difficult to do.

如果你采用你研究过的那种模型，对吧，就是会产生非平凡瞬态模式的那种。

If you take the kind of model that you worked on, right, which generate nontrivial transient patterns.

嗯哼。

Mhmm.

然后再加上高斯原理，即所谓的排他原理——如果局部秩序是由某种能量梯度维持的，而我被允许将你排除在那个空间位置之外，以获得更多空间。

And you add to that Gauss's principle, the so called exclusion principle, which is that if the local order is maintained by some energy gradient and I'm allowed to exclude you from that position in space so as to gain access to more of it.

确实会增加这些模式状态的出现频率。

Does increase the frequency of these pattern states.

所以达尔文称之为竞争，高斯称之为排他原理。

So Darwin called it competition, Gauss called it the exclusion principle.

所以你只需对一个原本相当简单的动力系统进行少量调整，就能产生非常长程的有序状态。

So you can add just a few tweaks to what would otherwise be a fairly simple dynamical system and produced very long term states of order.

至于它们为何会逐步升级，这一点目前还不太清楚。

And now why they then ratchet up, right, is is somewhat unknown.

嗯，我想这与我接下来要问的问题相关，就是关于你刚才提到的并非总能找到现成的涌现理论这一点。

Well, guess this this relates to what I was gonna ask next, which is about the you you already alluded to the fact that you don't always have an emergent theory lying around.

对吧？

Right?

当你面对一堆事物时，可能幸运地能用宏观可观测特征简单描述它，也可能不行。

When you have some collection of stuff, you may or may not be lucky enough to have a simple way of describing it just in terms of macroscopically observable features.

但当你能做到时，首先，我们对此了解多少？

But when you do well, so number one, what do we know about when you do?

比如，涌现描述的普遍性如何？

Like, how generic are emergent descriptions?

我们拥有这些描述是否已经非常幸运了？

Are we very fortunate to have them at all?

其次，我知道你曾撰写和谈论过噪声在维持这类现象中的作用，这让我非常着迷。

And and number two, I know that you've wrote and written and spoken on the role of noise in maintaining things like that, which is just fascinating to me.

你知道，我明白耗散和摩擦在宏观世界中无处不在，但你正在为它们对我们持续存在的积极贡献而非仅仅是烦扰做推销。

You know, I know I know that dissipation and friction are everywhere in the macroscopic world, but you're you're giving the sales pitch for us making them positive contributions to our persistence rather than merely annoyances.

是啊。

Yeah.

我是说，确实如此。

I mean, that's yeah.

就是那样，没错。

That was that yeah.

这有很多...好吧，我就不提那场辩论中的对手了

That's lots of well, I won't mention my adversaries in that debate

讲讲这个故事吧。

Tell the story.

讲讲这个故事吧。

Tell the story.

你可以讲出来。

You can tell it.

不。

No.

但这是我和大卫·沃尔珀特与丹尼·卡尼曼和卡斯·桑斯坦的一场辩论，他们写了这本名为《噪声》的书，讲述噪声有多么糟糕。

But this was a debate that David Wolpert and I had with Danny Kahneman and Cass Sunstein and and they had written this book called Noise and how terrible it is.

我是说，因为丹尼当然已经详细写过关于偏见的问题。

I mean, because Danny has written, of course, at length about bias Sure.

以及我们该如何纠正它。

And how we should correct it.

而这种续篇则是关于噪声以及我们该如何应对它。

And this sort of the sequel was noise and how we should correct it.

从进化论的角度来看，这种突变是复杂生命进化的必要条件，你知道的。

And and coming from evolutionary theory where this sort of sine qua non for the evolution of complex life is mutation, you know Yeah.

换句话说，噪声，这似乎有点不幸。

Noise in other words, it seemed a little bit unfortunate.

当然，当你从随机共振、随机放大、博弈中的均衡选择等角度来看时，噪声绝对是复杂系统最有价值的特性之一。

And then, of course, the more you look from, you know, stochastic resonance, stochastic amplification, you know, equilibrium selection in games, noise is absolutely one of the most valuable characteristics of complex systems.

如果你愿意，可以将其归结为一句话，即探索——当你想要探索一个空间时，噪声非常有用。

And if you want, you can reduce it to one statement, which is exploration, which is that if you want to explore a space, noise is very handy.

但当你想要利用某个解决方案时，你会希望稍微降低它的影响。

But once you want to exploit a solution, you wanna kinda turn it down a bit.

嗯。

Mhmm.

所以这就是复杂领域特有的高低温辩证关系。

And so it's this dialectic, right, between high and low temperature that is characteristic of the complex domain.

它既具有建设性又具有破坏性，但你需要能够控制它。

So it's both constructive and destructive, but you want to be able to control it.

那么当我们出现突发性描述时，它是否也起作用呢？

And does it play a role in when we have an emergent description?

嗯，我认为肯定有影响。

Well, I think it must.

对吧？

Right?

因为可以推测，这些新层次的起源很可能是通过某种随机游走过程被发现的。

Because presumably, the origin of those new levels presumably are discovered through some random walk of one kind or another.

而且，这也说明了突变本质上就是宏观层面的噪声。

And and it's also the case, right, that mutation is macroscopic noise.

我是说，按照物理学的标准来看。

I mean, by physics standards.

按照生物学的标准，则是微观噪声。

By biological standards, microscopic noise.

但你要知道，这可不是原子层面的噪声，对吧？

But, you know, this is not noise in an atom, right?

这是大分子层面的噪声。

This is noise in a macromolecule.

所以很有趣的是，自然界如何在超出我们通常认为的热噪声的层面上构建了噪声机制。

And so it's quite interesting how nature has built noise in at levels above what we'd normally think of as thermal noise.

而且这并非由温度轻微升高引起的噪声，尽管存在这些奥勒留效应。

And this is not the noise induced by a slight increase in temperature, even though there are these Aurelius Yeah.

这些实际上是人为构建的。

These are actually built.

它们是经过设计的骰子，我们将其加载到复杂系统中以产生变异性。

They're constructed dice that we've loaded complex systems with in order to generate variability.

在关于涌现现象的整个讨论中，不仅是今天，在我一生中，总存在这样一个问题：那些我们习以为常的概念，现在却需要我们去解释和说明，比如能动性、目的性等等。

In in this whole discussion of emergence, not just today, but in in my life, you know, there's always this issue that concepts we kind of take for granted are now things that we're trying to explain and account for, like agency or purpose or or whatever.

我突然想起你曾写过的一个话题，我很想多听听你的见解，那就是关于个体存在的问题。

I I just recalled one that you've written about that I would love to hear more about, which is the existence of individuals.

比如，我们如何将系统划分成'这是一个连贯整体'和'那是一个独立个体'？

Like, how do we get to carve up systems into this thing is a coherent whole and and that one is a separate thing?

你不会依赖于某种本质性的存在。

You're you're not going to rely on some fundamental essence.

你会说那是一种涌现现象。

You're to say that's an emergent phenomenon.

是的。

Yeah.

我是说，对个体性的兴趣来自两个不同的方向。

I mean, this interest in individuality comes from two different directions.

一个是我在牛津时不得不听理查德·道金斯坚称选择的唯一单位是基因。

One is when I was at Oxford having to listen to Richard Dawkins insist that the only unit of selection was a gene.

他的论点是基因是唯一具有时间连贯性的结构。

And his argument being that it's the only temporally coherent structure.

它是能在重组过程中完整保存下来的东西。

It's the thing that survives recombination intact.

所以当你洗牌时，保留的不是手牌，而是单张的牌。

So when you shuffle the deck of cards, it's not the hand that's preserved, it's the cards.

对吧？

Right?

这就是基因的观点。

So that's the gene.

那是他的看法。

That was his view.

这在我看来太过简单了。

And that seemed to me too simple minded.

另一方面，我们都有一种欲望，想要找到我们领域、我们学科的基本构成单元。

And then on the other hand, this desire that we all have to find the atomic building blocks of our field, of our domain.

可能是夸克，可能是原子，对吧，可能是分子，也可能是细胞。

So it could be a quark, it could be an atom, right, it could be a molecule, it could be a cell.

如果你对复杂性的演化感兴趣，至少在我看来，其中应该包括我们都习以为常的这个奇怪现象：复杂领域以我们称之为个体、行为体或生物体的这些‘包裹’形式存在。

And if you're interested in the evolution of of of complexity, at least to me, one of them should be this weird thing that we all take for granted, which is that the complex domain comes in these packages that we call individuals, agents, or organisms.

很难不注意到它们。

It's hard not to find them.

对吧？

Right?

我是说

I mean

视为理所当然。

Take it for granted.

发生什么事了？

What's going on?

是啊。

Yeah.

你知道吗？

You know?

我们是不是被误导了？

Are we just being misled?

这是名义上的吗？

Is it nominal?

这是感知上的假象吗？

Is it a perceptual artifact?

这些可能都是真的。

And all of that might be true.

对吧？

Right?

我是说，那可能是真的。

I mean, that might be true.

于是我和一些同事开始开发一种信息理论形式体系来寻找它们。

So with some colleagues, we started developing a information theoretic formalism to hunt for them.

对吧？

Right?

我们能否开发出，如果你愿意的话，像望远镜那样的透镜，它们工作在不同的电磁频率下，能够检测到不同类型的个体，这里的操作定义是指那些能够随时间向前传播适应性信息的东西。

Could we develop, if you like, lenses, like telescopes that work in different electromagnetic frequencies that would detect different kinds of individuals, a, where the operational definition is something that can propagate adaptive information forward in time.

一条适应性世界线，这就是我们在寻找的。

An adaptive world line, that's what we're looking for.

而且答案是肯定的，我们可以做到。

And and the answer is yes, we could.

我们发展了这个理论。

We developed this theory.

然后你会发现这类不同种类的代理原子，你知道的，个体。

And the and you discover this kind of zoo of different kinds of agentic atom, you know, individual.

我们最熟悉的个体就是生物体，其定义主要基于自身的谱系。

The one that we all know best, the organism, which is defined largely in terms of its own lineage.

对吧？

Right?

所以要理解肖恩，我该见见肖恩的父母；而要理解他们，又该见见他们的父母——并非要过度弗洛伊德化，但从表型上看，很多特质确实源自他们和环境，而从基因型看，几乎全部特质都来自他们。

So to understand Sean, I should meet Sean's parents and to understand them, their parents, not being excessively Freudian about it, but simply, phenotypically, lot of it comes from them and the environment, but a lot from them, genotypically, nearly all of it, actually.

全部都是。

All of it.

对吧？

Right?

不是表观遗传的，而是基因遗传的。

Not epigenetically, but genetically.

因此你是一个具有相当自主性的存在，主要负责将自己的信息在时间中传递下去。

And so you're this somewhat autonomous thing that is largely responsible for propagating your information forward in time.

如果观察像社会性昆虫这类生物，它们的遗传信息是由不同物理单元共享的。

If you look at things like social insects, well, there, the genetic information is shared across different physical units.

对吧？

Right?

所以蚂蚁和蜜蜂的情况可能是，蜂后负责传递基因组，工蜂则协助她。

So ants and bees, it might be that the queen bee propagates the genome, the workers help her.

在那里，个体性的概念有所不同，它是一种集体性的概念。

There, there's a different conception of individuality, and it's a collective one.

而这些信息理论工具的作用就是发现它们。

And so what these information theoretic devices do is they find them.

它们会说，啊，这就是信息在某种意义上得以传递的适当聚合层级。

They say, ah, that's the right level of aggregation at which information is in some sense being propagated forward.

这就是一个足够粗粒度的划分。

It's it's that's the that's a coarse graining which is sufficient.

那么现在既然已经发现了这些，让我们回到理查德·道金斯的观点。

So now having discovered them, let's go back to Richard Dawkins.

你会意识到，事实上，能够可靠地随时间传递的并非最基础的构建模块。

What you realize, right, is that it's not true that it's the most minimal building block that is reliably transmitted forward in time.

结果发现它有点周期性。

It turns out it's kinda periodic.

最基础的事物是稳定的，而稍具包容性的事物则不然。

The minimal things are, then the things a bit more inclusive are not.

嗯。

Mhmm.

那么更具包容性的事物就是对的，对吧？

Then the things that are more inclusive are right?

你明白我的意思吗？

You see what I mean?

这有点像社会。

And so a little bit like a society.

一个社会很可能相当可靠地传承文化，如果你衡量的是这一点的话。

A society probably propagates forward culture quite reliably, if that's what you were measuring.

但其中的某些部分不会传承，而个体可能会。

But bits of it do not, and individuals might.

因此对我们来说，这只是一次更为务实的尝试，旨在发现复杂系统中的因果单元。

And so for us, it was just a much more grounded attempt to discover the causal units of complex systems.

我想可以这么说。

I guess that's how I would say it.

那么在某些情况下，是否应该将蚁群视为个体，而非单只蚂蚁？

So under some circumstances, is it right to think of the ant colony as the individual rather than the individual ants?

正是如此。

Exactly.

完全正确。

Absolutely right.

你知道，我是说，这是一种真正良好的协作关系。

You know, I mean, a a really good collaboration.

对吧？

Right?

就像吉姆·默里在量子宇宙学研究中那样，他们本身就是那个个体。

So like Jim Murray on on on their quantum cosmology, they are the individual.

如果将其一分为二，你就会失去它。

And cutting it in half, you would lose it.

我认为这正是赫伯特·西蒙在他七十年代发表的两篇论文《复杂性的架构》和《复杂性的组织》中试图探讨的观点之一——这些松散联结的个体与紧密联结的聚合体之间存在着动态转换。

And I think that's one of the things that Herb Simon was trying to talk about in his two papers, the architecture of complexity and the organization of complexity published in the seventies, which was you have these loosely bound things and these tightly bound aggregates, and you move between them.

我认为这是复杂系统最迷人的特性之一：那些看似物理联结松散的结构，实际上形成了高度紧密的聚合体。

And I think that's one of the really fascinating characteristics of complex systems that you form these quite tightly bound aggregates that look physically loosely bound.

圣塔菲研究所出版社是否出版过复杂系统研究史上核心论文的合集？

Has SFI press ever published an anthology of the most important central papers in the history of complex systems?

嗯，那一定是这样的。

Well, that must be yes.

我现在正在发表它。

I am publishing it now.

我知道。

I know it.

你确实知道你可以知道。

You could you know it.

所以我们将在SFI成立四十周年之际出版《复杂性科学基础》，也就是明年。

So we are publishing at on the fortieth anniversary of SFI, which is next year, foundations of complexity science.

太好了。

Lovely.

这些都是论文。

And these are papers.

前两篇论文是洛特卡和齐拉特在1920年代至2000年间的作品。

The first two papers are Lotka and Zilard, nineteen twenty nineteen twenties through to 2000.

所以我不涉及史前时期，只做历史部分。

And so I don't do the prehistory, do the history.

这是一个非常连贯的项目。

And it's it's it's an extraordinary coherent project.

在SFI开会时我们常开玩笑说，无论是招聘还是决策时都会想：天哪。

The one of the things that we always laugh about at SFI when we have meetings and we're trying to hire people or whatever or decide, we would think, oh my god.

我们中没人能就复杂性的定义达成一致。

None of us agree on what complexity is.